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Found 938 result(s)
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The Universidad del Rosario Research data repository is an institutional iniciative launched in 2019 to preserve, provide access and promote the use of data resulting from Universidad del Rosario research projects. The Repository aims to consolidate an online, collaborative working space and data-sharing platform to support Universidad del Rosario researchers and their collaborators, and to ensure that research data is available to the community, in order to support further research and contribute to the democratization of knowledge. The Research data repository is the heart of an institutional strategy that seeks to ensure the generation of Findable, Accessible, Interoperable and Reusable (FAIR) data, with the aim of increasing its impact and visibility. This strategy follows the international philosophy of making research data “as open as possible and as closed as necessary”, in order to foster the expansion, valuation, acceleration and reusability of scientific research, but at the same time, safeguard the privacy of the subjects. The platform storage, preserves and facilitates the management of research data from all disciplines, generated by the researchers of all the schools and faculties of the University, that work together to ensure research with the highest standards of quality and scientific integrity, encouraging innovation for the benefit of society.
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Etsin is a research data finder that contains descriptive information – that is, metadata – on research datasets. In the service you can search and find data from various fields of research. A researcher, research group or organisation can use Etsin to publish information on their datasets and offer them for wider use. The metadata contained in Etsin makes it easy for anyone to discover the datasets. Etsin assigns a permanent URN identifier to datasets, making it possible to link to the dataset and gather merit through its publication and use. The metadata enables users to search for datasets and evaluate the potential for reuse. Etsin includes a description of the dataset, keywords and various dataset identifiers. The dataset information includes, for example, its subject, language, author, owner and how it is licensed for reuse. Good description of data plays an important role in its discoverability and visibility. Etsin encourages comprehensive descriptions by adapting a common set of discipline independent metadata fields and by making it easy to enter metadata. Etsin only collects metadata on datasets, not the data themselves. Anyone may browse and read the metadata. Etsin can be used with a browser or through an open interface (API). The service is discipline independent and free to use. Etsin is a service provided by the Ministry of Education and Culture to actors in the Finnish research system. The service is produced by CSC – IT Center for Science (CSC). Customer service contacts and feedback is available through servicedesk@csc.fi. The service maintenance window is on the fourth Monday of every month between 4 and 6 PM (EET). During that time, the service will be out of use.
BindingDB is a public, web-accessible knowledgebase of measured binding affinities, focusing chiefly on the interactions of proteins considered to be candidate drug-targets with ligands that are small, drug-like molecules. BindingDB supports medicinal chemistry and drug discovery via literature awareness and development of structure-activity relations (SAR and QSAR); validation of computational chemistry and molecular modeling approaches such as docking, scoring and free energy methods; chemical biology and chemical genomics; and basic studies of the physical chemistry of molecular recognition. BindingDB also includes a small collection of host-guest binding data of interest to chemists studying supramolecular systems. The data collection derives from a variety of measurement techniques, including enzyme inhibition and kinetics, isothermal titration calorimetry, NMR, and radioligand and competition assays. BindingDB includes data extracted from the literature and from US Patents by the BindingDB project, selected PubChem confirmatory BioAssays, and ChEMBL entries for which a well defined protein target ("TARGET_TYPE='PROTEIN'") is provided.
The BioCyc database collection of Pathway/Genome Databases (PGDBs) provides a reference on the genomes and metabolic pathways of thousands of sequenced organisms. BioCyc PGDBs are generated by software that predict the metabolic pathways of completely sequenced organisms, predict which genes code for missing enzymes in metabolic pathways, and predict operons. BioCyc also integrates information from other bioinformatics databases, such as protein feature and Gene Ontology information from UniProt. The BioCyc website provides a suite of software tools for database searching and visualization, for omics data analysis, and for comparative genomics and comparative pathway questions. From 2016 on, access to the EcoCyc and MetaCyc databases will remain free. Subscriptions to the other 7,600 BioCyc databases will be available to institutions (e.g., libraries), and to individuals. Access to licensed databases via: https://biocyc.org/Product-summary.shtml.
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Androgen Receptor Gene Mutations Database is for all who are interested in mutations of the Androgen Receptor Gene. In light of the difficulty in getting new AR mutations published the curator will now accept new mutations that have not been published, provided that it is from a reputable research or clinical laboratory. The curator also strongly suggests that where possible, particularly in the case of new unique mutations that an attempt be made to at least confirm the pathogenicity of the putatative mutation, by showing that the mutation when transfected into a suitable expression system produces a mutant androgen receptor protein.
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Bacteriome.org is a database integrating physical (protein-protein) and functional interactions within the context of an E. coli knowledgebase.
ViralZone is a SIB Swiss Institute of Bioinformatics web-resource for all viral genus and families, providing general molecular and epidemiological information, along with virion and genome figures. Each virus or family page gives an easy access to UniProtKB/Swiss-Prot viral protein entries.
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The nature of the ‘Bridge of Data’ project is to design and build a platform that allows collecting, searching, analyzing and sharing open research data and to provide it with unique data collected from the three most important Pomeranian universities: Gdańsk University of Technology, Medical University of Gdańsk and the University of Gdańsk. These data will be made available free of charge to the scientific community, entrepreneurs and the public. A bridge will be built to allow reuse of Open Research Data. The available research data will be described by standards developed by dedicated, experienced scientific teams. The metadata will allow other external computer systems to interpret the collected data. ORD descriptions will also include data reuse or reduction scenarios to facilitate further processing.
The PRIDE PRoteomics IDEntifications database is a centralized, standards compliant, public data repository for proteomics data, including protein and peptide identifications, post-translational modifications and supporting spectral evidence. PRIDE encourages and welcomes direct user submissions of mass spectrometry data to be published in peer-reviewed publications.
Fishbase is a global species database and encyclopedia of over 30,000 species and subspecies of fishes that is searchable by common name, genus, species, geography, family, ecosystem, references literature, tools, etc. Links to other, related databases such as the Catalog of Fishes, GenBack, and LarvalBase. Associated with a partner journal, Acta Ichthyologica et Piscatoria. With mirror sites in English, German, French Spanish, Portuguese, French, Swedish, Chinese and Arabian language.
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<<<!!!<< With the implementation of GlyTouCan (https://glytoucan.org/) the mission of GlycomeDB comes to an end. >>>!!!>>> With the new database, GlycomeDB, it is possible to get an overview of all carbohydrate structures in the different databases and to crosslink common structures in the different databases. Scientists are now able to search for a particular structure in the meta database and get information about the occurrence of this structure in the five carbohydrate structure databases.